Spectrum availability at frequencies that can be economically used for wireless communications may be unsatisfactory. This problem may become apparent, for example, when referring to the FCC (Federal Communications Commission) frequency chart. The FCC frequency chart indicates multiple allocations over all available frequency bands. As a result, there is competition for the use of spectra, such as in the bands below 3 GHz. However, according to D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radios”, 38th Annual Asilomar Conference on Signals, Systems and Computers, November 2004, actual measurements taken in an urban setting may reveal a typical utilization of 0.5% in the 3-4 GHz frequency band. The utilization may even drop to 0.3% in the 4-5 GHz band. Thus, spectrum shortage may partially be the result of regulatory and licensing processes.
The current approach for spectrum sharing is regulated so that wireless systems are assigned fixed spectrum allocations, operating frequencies and bandwidths, with constraints on power emission that may limit their range. Therefore, some communications systems may be designed to achieve the best possible spectrum efficiency within the assigned bandwidth using sophisticated modulation, coding, multiple antennas, and other techniques. The most advanced systems are approaching Shannon's channel capacity limit, so further increases in capacity would require additional system bandwidth. On the other hand, the discrepancy between spectrum allocation and spectrum use suggests that spectrum shortage could be overcome by allowing more flexible usage of a spectrum. Flexibility could mean that radio terminals could find and adapt to any immediate local spectrum availability.
Notice of Proposed Rule Making and Order, December 2003, a new radio class, so-called “cognitive radio”, is described, that may be able to reliably sense the spectral environment over a wide bandwidth, detect the presence/absence of legacy users (primary users), and use the spectrum only if the communication does not interfere with primary users.
In general, a cognitive radio—as its name implies—carries a level of cognition or intelligence that permits decision-making and learned patterns of behaviour. According to the Institute of Electrical and Electronics Engineers (IEEE), the cognitive radio may be a radio transmitter that is designed to intelligently detect whether a particular segment of the radio spectrum is currently in use and to jump into (or out of) a temporarily unused spectrum very rapidly without interfering with transmissions of other users. To achieve this, the wireless network or a wireless node itself may be configured to change particular transmission parameters to execute tasks efficiently without interfering with licensed users. The parameter alteration may be based on observations of several factors, such as, for example, radio frequency spectrum, user behaviour, network state etc., so that the radio spectrum may be utilized more efficiently. More specifically, the radio transmitter (e.g., mobile terminal, mobile phone, user equipment, or the like) may be configured to scan its environment, decide on the best frequency band as well as transmission standard, and indicate to the other connection end (e.g., base station, access node, or the like) which transmit power, channel pre-equalization and pre-coding schemes should be used.
The cognitive radio concept may utilize flexible implementation on various layers. The physical layer may require more flexibility than currently known from traditional non-cognitive radio standards. This flexibility may be achieved for the physical layer baseband processing by a software defined radio (SDR) implementation. SDRs may rely on embedded software for their functionality and configuration. Assuming it is clear which task a user wants to solve (voice call, data download, location tracking etc.), the cognitive radio may select a corresponding technology (e.g., Global System for Mobile communication (GSM), Wireless Local Area Network (WLAN), Global Positioning System (GPS) etc.).
In application specific integrated circuit (ASIC) implementations for conventional non-cognitive radios, the most critical case for wireless channel estimation plus channel decoding may be assumed, and thus maximum possible algorithm performance may be targeted by implementing algorithms for a worst case scenario, which may require high complexity. As already mentioned above, in cognitive radios, a spectrum scanner may identify available spectrum resources and provide this information to a cognitive radio transmitter for corresponding transmission parameter selection.
FIG. 2 shows a graph indicating processor load for different radio algorithms (decoding, channel estimation, frequency synchronization and timing synchronization) running concurrently on a floating point digital signal processor (DSP) of an orthogonal frequency division multiplexing (OFDM) SDR. It can be seen that channel estimation and decoding algorithms may require the most DSP processor load in this OFDM radio. The more critical the channel properties are, the more sophisticated baseband algorithms may need to be used for channel estimation and channel decoding. This may lead to high processing loads and corresponding high power consumption, which may be undesirable in certain situations, such as for some mobile terminals.